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Using a large repository of genetic data and birth-record data from Finland, an international team of researchers has assembled one of the most comprehensive views of a population's evolutionary genetics to date. They provide a very fine-scale resolution of the genetic history and demographics of the Finnish population covering the last 100 generations — the timespan during which most disease-causing variants emerged.

In a study published recently in the , the authors combine Finnish population data with “haplotype” data from 43,254 Finns, resulting in high-resolution migration maps and evolutionary origins of rare-disease variants. A haplotype is a group of genes, or a cluster of variations on a DNA sequence, which is inherited as a group from a common ancestor. Analyzing haplotypes helps scientists identify patterns of genetic variations associated with disease states.

Haplotype-based genetic analysis combined with birth record data enabled the researchers to derive a complete picture of Finland’s recent ancestry, population size changes, interbreeding between isolated populations, and their migration patterns.

Alicia Martin, a postdoctoral researcher in Mark Daly’s lab in Massachusetts General Hospital and the Stanley Center at ӳ����ý of MIT and Harvard, discussed the value of using haplotype data in disease research, as well as the future of similar studies in other countries. 

Alicia Martin

Why did you choose Finland for this study?

Alicia Martin: Finland went through a series of “bottleneck” events in the past. These are events like natural calamities or human activities which drastically reduce the size of a population. This typically results in “founder” populations, which remain deprived of genetic variation among surviving individuals.

Finland is representative of a founder population which has historically been isolated from other European countries. This isolation helped us identify harmful mutations contributing to Finnish-specific or frequently occurring diseases. The ability to trace these mutations, where they first originated, how they evolved and spread across the country, became the most powerful aspect of this study.

Overall, it is a great place to investigate population history or disease genetics because of its isolation through multiple bottleneck events, their national engagement in genetics research, unified health records, and detailed historical and birth records available within Finland and neighboring countries.

Why analyze haplotypes?

Martin: Haplotype-based analysis has been used in genetics research for decades. However, this was one of the first studies to use it at the scale of tens of thousands of individuals. Finns, being an isolated population, share a lot more haplotypes on average than other populations do.

Analyzing haplotypes helps us integrate our views of both common and rare variants so we can understand and disentangle the genetic architecture of complex diseases, which have a wide spectrum of frequencies and effect sizes.

Do you think other genome-wide association studies (GWAS) will use haplotype-based analyses in future?

Martin: Although whole genome or exome (protein-coding genes of the genome) sequencing data can provide insights into population changes, it is usually at the scale of hundreds to thousands of generations ago. On the contrary, haplotypes give insights into the last couple of hundred generations only — providing insight into the relatively fine scale and recent history. That is really the time span which is critical for disease variants to arise and persist in the population.

We find that haplotype sharing is notably higher among rare harmful variations. Thus we advocate for its use in readily available large repositories of GWAS data, as a tremendous shortcut to assess the role of rare variations in disease.

Bypassing whole-genome sequencing for this purpose is especially appealing, as current costs of data generation and the sample sizes necessary to determine rare non-coding variants in disease are indeed prohibitive.

What did you learn about disease through this study?

Martin: Disease-specific rare variants appeared more frequently in the Finnish population when they went through recurrent bottleneck events in the past. We were able to trace the rise and spread of these variants known to confer Finnish-specific diseases (for example, congenital chloride diarrhea).

This was made possible by using the significantly efficient and cost-effective haplotype-based analysis methods in comparison to whole genome or exome sequencing-based approaches.

What are the future implications of this particular study?

Martin: We learned detailed information about how the Finnish population expanded over time and how some cultural events or features acted as barriers or accelerants to these types of population events.

For example, Vaasa is a bilingual city where inhabitants speak both Swedish and Finnish. The population from Vaasa shares similar haplotypes almost exclusively with nearby communities. That’s most likely driven by linguistic differences. People from Vaasa do not share a lot of haplotypes all around Finland since these linguistic patterns are primarily isolated to this western region right around the city.

As Finnish and other national genotyping efforts are underway and likely to reach hundreds of thousands of individuals in short order, we expect our work to serve as a population history reference for years to come.

What are you working on next?

Martin: We are interested in applying this similar study framework to other more globally diverse areas of the world, for example, Africa. Everything about human demography originated in Africa, and their population history is much more complex. Being able to use these haplotype-based genetic analyses to disentangle Africa’s recent population history will be very interesting. It will help us see how genes flowed and how populations intermixed and exchanged genetic material over time — especially when these records are not abundantly available in Africa.